P929: CIRCULATING TUMOR DNA ASSESSMENT IMPROVES PROGNOSTIC PREDICTION IN RELAPSED/REFRACTORY MULTIPLE MYELOMA RECEIVING IXAZOMIB, LENALIDOMIDE, AND DEXAMETHASONE
Authors: Yasunori Kogure, Hiroshi Handa, Yuta Ito, Masaki Ri, Yuichi Horigome, Masaki Iino, Yoriko Harazaki, Takahiro Kobayashi, Masahiro Abe, Tadao Ishida, Shigeki Ito, Hiromi Iwasaki, Junya Kuroda, Hirohiko Shibayama, Kazutaka Sunami, Hiroyuki Takamatsu, Hideto Tamura, Toshiaki Hayashi, Kiwamu Akagi, Tomohiro Shinozaki, Takahiro Yoshida, Ikuo Mori, Shinsuke Iida, Takahiro Maeda, Keisuke Kataoka
Journal: HemaSphere (2023)

Topic: 14. Myeloma and other monoclonal gammopathies - Clinical Background: Although multiple myeloma (MM) is characterized by many driver mutations, their prognostic impact is limited in newly diagnosed MM. However, it remains elusive how driver mutations, including those detected in circulating tumor DNA (ctDNA), affect prognosis in relapsed/refractory MM (RRMM). Aims: We aim to characterize the landscape of somatic alterations and their prognostic impact in RRMM, using bone marrow plasma cells (BMPC) and ctDNA samples obtained from patients treated with ixazomib, lenalidomide, and dexamethasone (IRd) therapy. Methods: We performed targeted-capture sequencing of bone marrow plasma cell (BMPC) and ctDNA of 261 RRMM cases enrolled onto a multicenter, prospective, observational study (C16042 study; JapicCTI-183860), where patients were uniformly treated with IRd. All patients provided written informed consent. We obtained 163 BMPC and 259 ctDNA samples at the initiation of IRd. Fluorescence in situ hybridization analyses of high-risk cytogenetic abnormalities were also performed. Results: Recurrent mutations were observed in 24 and 47 genes in BMPC and ctDNA, respectively. As reported, KRAS was most frequent, followed by NRAS, TP53, DIS3, and BRAF in BMPC. On the other hand, mutations related to clonal hematopoiesis (CH) were frequently observed in ctDNA, including those affecting DNMT3A, TET2, PPM1D, and ASXL1. Besides them, TP53 was most common, followed by KRAS, BRAF, ATM, NRAS, and DIS3. When BMPC-seq and ctDNA-seq data were combined, TP53 was most frequent (30.4%), followed by KRAS (21.7%), DNMT3A (16.1%), TET2 (15.5%), NRAS (14.3%), BRAF (10.6%), DIS3 (10.6%), PPM1D (8.1%), and ATM (5.6%). In addition to CH-associated genes, varying proportion of mutations were exclusively detected in ctDNA, particularly in TP53 (59.2%), in which subclonal mutations are more common than in other genes. Then, we assessed the effects of somatic alterations on patient prognosis in RRMM. In univariable analyses, BMPC mutations of TP53 (HR [95% CI]; 3.0 [1.8-5.1]) and KRAS (2.0 [1.3-3.2]) were associated with inferior PFS. However, ctDNA mutations were more impactful: ctDNA mutations of KRAS (HR [95% CI]; 4.4 [2.8-7.1]), TP53 (2.3 [1.6-3.3]), DIS3 (2.5 [1.3-4.7]), BRAF (2.4 [1.3-4.6]), NRAS (2.6 [1.3-5.2]), and ATM (1.9 [1.0-3.6]) were associated with worse PFS. Moreover, only mutations detected in both BMPC and ctDNA have a prognostic impact for KRAS. A total number of ctDNA mutations in the six genes significantly affected prognosis; the 2-year PFS was 57.3%, 22.7%, and 0% for those with 0, 1, and ≥ 2 mutations, respectively. Multivariable analysis showed the number of the six ctDNA mutations was a strong prognostic predictor, independent of clinical factors and cytogenetic abnormalities (HR [95% CI]: 3.4 [1.9–6.1] and 2.1 [1.3–3.5] for number ≥ 2 and 1, respectively) in 161 RRMM cases with both BMPC-seq and ctDNA-seq data. We then developed a prognostic index using the number of the six significant ctDNA mutations and clinical factors (ctRRMM-PI), which classifies patients into three categories with 2-year PFS of 63.1%, 27.1%, and 0% (Figure). The ctRRMM-PI was successfully validated by the remaining 98 RRMM cases without BMPC-seq data. Summary/Conclusion: We have clarified the genetic properties of ctDNA mutations and their superiority over BMPC mutations in prognostic prediction in RRMM. These findings have led to the development of a new prognostic scoring system incorporating ctDNA mutations and clinical factors. Therefore, molecular profiling with ctDNA mutations can accurately identify high-risk populations and improve patient management strategy in RRMM.Keywords: Multiple myeloma, Somatic mutation, Prognostic factor, ctDNA